Asymptotic Normality of the Estimators for Fractional Brownian Motions with Discrete Data
This paper deals with the problem of estimating the Hurst parameter in the fractional Brownian motion when the Hurst index is greater than one half. The estimation procedure is built upon the marriage of the autocorrelation approach and the maximum likelihood approach. The asymptotic properties of t...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2014/323091 |
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| _version_ | 1850168573648961536 |
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| author | Lin Sun Xiaojian Yu Xuewei Guan Qinghao Meng |
| author_facet | Lin Sun Xiaojian Yu Xuewei Guan Qinghao Meng |
| author_sort | Lin Sun |
| collection | DOAJ |
| description | This paper deals with the problem of estimating the Hurst parameter in the fractional Brownian motion when the Hurst index is greater than one half. The estimation procedure is built upon the marriage of the autocorrelation approach and the maximum likelihood approach. The asymptotic properties of the estimators are presented. Using the Monte Carlo experiments, we compare the performance of our method to existing ones, namely, R/S method, variations estimators, and wavelet method. These comparative results demonstrate that the proposed approach is effective and efficient. |
| format | Article |
| id | doaj-art-a7cb3dd38b154a729a2a44f9a7523866 |
| institution | OA Journals |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-a7cb3dd38b154a729a2a44f9a75238662025-08-20T02:20:56ZengWileyAbstract and Applied Analysis1085-33751687-04092014-01-01201410.1155/2014/323091323091Asymptotic Normality of the Estimators for Fractional Brownian Motions with Discrete DataLin Sun0Xiaojian Yu1Xuewei Guan2Qinghao Meng3School of Applied Mathematics, Guangdong University of Technology, Guangzhou 510520, ChinaSchool of Economics and Commerce, South China University of Technology, Guangzhou 510006, ChinaSchool of Business Administration, South China University of Technology, Guangzhou 510640, ChinaSchool of Business Administration, South China University of Technology, Guangzhou 510640, ChinaThis paper deals with the problem of estimating the Hurst parameter in the fractional Brownian motion when the Hurst index is greater than one half. The estimation procedure is built upon the marriage of the autocorrelation approach and the maximum likelihood approach. The asymptotic properties of the estimators are presented. Using the Monte Carlo experiments, we compare the performance of our method to existing ones, namely, R/S method, variations estimators, and wavelet method. These comparative results demonstrate that the proposed approach is effective and efficient.http://dx.doi.org/10.1155/2014/323091 |
| spellingShingle | Lin Sun Xiaojian Yu Xuewei Guan Qinghao Meng Asymptotic Normality of the Estimators for Fractional Brownian Motions with Discrete Data Abstract and Applied Analysis |
| title | Asymptotic Normality of the Estimators for Fractional Brownian Motions with Discrete Data |
| title_full | Asymptotic Normality of the Estimators for Fractional Brownian Motions with Discrete Data |
| title_fullStr | Asymptotic Normality of the Estimators for Fractional Brownian Motions with Discrete Data |
| title_full_unstemmed | Asymptotic Normality of the Estimators for Fractional Brownian Motions with Discrete Data |
| title_short | Asymptotic Normality of the Estimators for Fractional Brownian Motions with Discrete Data |
| title_sort | asymptotic normality of the estimators for fractional brownian motions with discrete data |
| url | http://dx.doi.org/10.1155/2014/323091 |
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